A method for converting a rectilinear image and a focal length into a cylindrical image parameterized by a height of the cylinder and an angular distance in a single buffer on a remote processing device. The method, on the remote processing device, comprising joining two or more images together to form a panoramic image with corrected perspective. The rectilinear transformation is "in-place" and requires only one buffer. Color correction and motion estimation is also carried out on the remote device. In an alternate embodiment, a computer readable medium corresponding to the above method is described.
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1. A method for converting a rectilinear image and a focal length into a cylindrical image parameterized by a height of the cylinder and an angular distance in a single buffer on a remote processing device, the method comprising the steps of:
collecting a source rectilinear image in a single buffer from a camera; dividing the single buffer with a first end and a second end, into a series of successive scan lines of predetermined width, the single buffer containing the source rectilinear image; grouping the series of scans lines, into two groups, a first group of adjacent scan lines having a first boundary at the first end of the buffer and a second boundary at a predetermined position of an angular distance, and a second group of scan lines defined by the remainder of the scan lines within the single buffer not within the first group, transforming each scan line divided into the first and second group from rectilinear coordinates to cylindrical coordinates comprising the successive sub-steps of: (a) reading each source scan; (a.1) wherein each successive source scan line in the first group is read from the buffer at a position starting from the first end and continuing to the predetermined angular position; (a.2) wherein each source scan line in the second group is read from the buffer at a position starting from the second end and continuing to the predetermined angular position; (b) transforming each scan line read from rectilinear coordinates to cylindrical coordinates; and (c) writing each scan line transformed back into the buffer at the position in the buffer from where the source scan line was read; and (d) repeating the sub-steps (a) through (e) above until all the scan lines have been transformed. 10. A method for converting a rectilinear image parameterized by an optical center (x_ctr, y_ctr) and a focal length (f) into a cylindrical image parameterized by a height (h) and an angular distance (_) in a single buffer on a remote processing device, the method comprising the steps of:
collecting a source rectilinear image in a single butter from a camera; dividing the single buffer with a first end and a second end, into a series of successive scan lines of predetermined width, the single buffer containing the source rectilinear image; grouping the series of scans lines, into two groups, a first group of adjacent scan lines having a first boundary at the first end of the buffer and a second boundary at a predetermined position of an angular distance, and a second group of scan lines defined by the remainder of the scan lines within the single buffer not within the first group; reading a source scan line at a location (col_src) on the rectilinear source image from the single buffer so that col_src=x_src+x_ctr; transforming the source rectilinear scan line (x_src, y_src) into a destination cylindrical scan line (x_dst, y_dst) based on: a location of each vertical scanline as defined by the equation: where col_src=f*tan _+x_ctr; and col_dst is a destination column location in the buffer; a scale factor for each source scan line (y_src) defined by the equation:
where _min=a tan2(-x_src, f); _max=a tan2(width-x_src, f); width is the width of the source rectilinear image; and writing the cylindrical scan line at a location (col_dst) in the buffer.
11. A computer readable medium containing programming instructions for converting a rectilinear image and a focal length into a cylindrical image parameterized by a height of the cylinder and an angular distance in a single buffer on a remote processing device, the programming instructions comprising:
collecting a source rectilinear image in a single buffer from a camera; dividing the single buffer with a first end and a second end, into a series of successive scan lines of predetermined width, the single buffer containing the source rectilinear image; grouping the series of scans lines, into two groups, a first group of adjacent scan lines having a first boundary at the first end of the buffer and a second boundary at a predetermined position of an angular distance, and a second group of scan lines defined by the remainder of the scan lines within the single buffer not within the first group; transforming each scan line divided into the first and second group from rectilinear coordinates to cylindrical coordinates comprising the successive sub-steps of: (a) reading each source scan; (a.1) wherein each successive source scan line in the first group is read from the buffer at a position starting from the first end and continuing to the predetermined angular position; (a.2) wherein each source scan line in the second group is read from the buffer at a position starting from the second end and continuing to the predetermined angular position; (b) transforming each scan line read from rectilinear coordinates to cylindrical coordinates; and (c) writing each scan line transformed back into the buffer at the position in the buffer from where the source scan line was read; and (d) repeating the sub-steps (a) through (c) above until all the scan lines have been transformed. 2. The method according to
3. The method according to
downsampling a first image in a first direction and in a second direction; downsampling a second image in the first direction and in the second direction; filtering the first and the second image so as to filter out any global illumination changes between the first image and the second image; calculating a first displacement along the first direction between the first downsampled image along the first direction and the second downsampled image along the first direction; and calculating a second displacement along the second direction between the first downsampled image along the second direction and the second downsampled image along the second direction.
4. The method according to
converting a pair of images from rectangular coordinates to cylindrical coordinates to create a first image and a second image.
5. The method according to
6. The method according to
accumulating the sum-of-absolute-differences (SAD) between a predefined area of the first image and a predefined area of the second image.
7. The method according to
receiving a color channel from at least the first image and the second image; creating an overlap portion between the first image and second image; and adjusting the color channel for the first image and for the second image in at least the overlap portion between the first image and the second image which is independent of motion estimation.
8. The method as according to
computing the brightness (B1) and contrast (C1) for the first color channel; computing the brightness (B2) and contrast (C2) for the second color channel; adjusting color correction in at least the overlap portion between the first image and the second image; setting the color channel for the first image is set equal to: I1=B1+C1×I1; and setting the color channel for the second image is set equal to I2=B2+C2×I2.
9. The method according to
computing a histogram of color distribution for the first color channel (H1); computing a histogram of color distribution for the second color channel (H2); and setting B1 and B2 equal to: H2-(matched contrast (C))×H1 wherein the C is set equal to the square root of a variance calculated for H1 divided by a variance calculated for H2.
12. The computer readable medium according to
13. The computer readable medium according to
downsampling a first image in a first direction and in a second direction; downsampling a second image in the first direction and in the second direction; filtering the first and the second image so as to filter out any global illumination changes between the first image and the second image; calculating a first displacement along the first direction between the first downsampled image along the first direction and the second downsampled image along the first direction; and calculating a second displacement along the second direction between the first downsampled image along the second direction and the second downsampled image along the second direction.
14. The computer readable medium according to
converting a pair of images from rectangular coordinates to cylindrical coordinates to create a first image and a second image.
15. The computer readable medium according to
16. The computer readable medium according to
accumulating the sum-of-absolute-differences (SAD) between a predefined area of the first image and a predefined area of the second image.
17. The computer readable medium according to
receiving a color channel from at least the first image and the second image; creating an overlap portion between the first image and second image; and adjusting the color channel for the first image and for the second image in at least the overlap portion between the first image and the second image which is independent of motion estimation.
18. The computer readable medium according to
computing the brightness (B1) and contrast (C1) for the first color channel; computing the brightness (B2) and contrast (C2) for the second color channel; adjusting color correction in at least the overlap portion between the first image and the second image; setting the color channel for the first image is set equal to: I1=B1+C1×I1; and setting the color channel for the second image is set equal to I2=B2+C2×I2.
19. The computer readable medium according to
computing a histogram of color distribution for the first color channel (H1); computing a histogram of color distribution for the second color channel (H2); arid setting B1 and B2 equal to: H2-(matched contrast (C))×H1 wherein the C is set equal to the square root of a variance calculated for H1 divided by a variance calculated for H2.
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This application relates to technology similar to U.S. patent applications Ser. No. 09/477,037, Ser. No. 09/477,036, Ser. No. 09/476,652, now U.S. Pat. No. 6,456,323 Ser. No. 09/477,919, and Ser. No. 09/477,117, all being filed concurrently herewith and commonly assigned herewith to STMicroelectronics Inc. and which are hereby incorporated by reference in their entirety hereinto.
All of the material in this patent application is subject to copyright protection under the copyright laws of the United States and of other countries. As of the first effective filing date of the present application, this material is protected as unpublished material.
However, permission to copy this material is hereby granted to the extent that the copyright owner has no objection to the facsimile reproduction by anyone of the patent documentation or patent disclosure, as it appears in the United States Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.
1. Field of the Invention
The invention disclosed broadly relates to the field of image processing and more specifically to image processing in a digital camera for taking panoramic pictures.
2. Description of the Related Art
Today, panoramic photography is accomplished in various ways. One is to use a still camera mounted on a tripod to take a succession of shots as the camera is pivoted around the tripod. In some cameras, a wider than usual strip of film is exposed with special movable optics.
In other cameras, conventional format film, such as 35 mm film, is masked during the exposure in the camera to provide a panoramic effect. The effect is panoramic but the whole exposure is limited by the field of view through the lens.
Other techniques for creating panoramic photography include to physically cut and paste together strips of exposed film by carefully aligning boundaries between edges of film.
The benefits of electronic photography have led to the growth of digital cameras, that, unlike their film-based counterparts, store images captured in memory into digital memory such as flash memory. To provide panoramic photography effects, these digital cameras can interface with personal computers for joining together two or more images into one image to provide a panoramic effect by joining edge boundaries of images. One such system is disclosed in U.S. Pat. No. 6,682,197, by named inventors Omid A. Moughadam, Stuart R. Ring, and John R. Squilla, entitled "Electronic Panoramic Camera For Use With An External Processor."
Complicated panoramic digital cameras are available that rely on position sensors or satellite communications for determining position coordinates. These position coordinates are used to help combine the panoramic images. The process of combining scenes taken from different camera orientations is known as "Image Stitching." One such system is disclosed in U.S. Pat. No. 5,262,867 by named inventor Kiyonobu Kojima entitled "Electronic Camera and Device for Panoramic Imaging and Object Searching" issued on Nov. 16, 1993.
A panoramic camera with a memory device for storing data from a previously photographed portion of an object and a control device for enabling the display device to substantially display both the image to be photographed and the image already photographed and stored in the memory space is described in U.S. Pat. No. 5,138,460 by named inventors Egawa and Akira entitled "Apparatus for forming Composite Images" issued on Aug. 11, 1992.
Although these techniques are useful, they are not without their shortcomings. One shortcoming is the expense and complication arising from the need for orientation and position sensors for determining picture orientation. Accordingly, a need exists for a device and method to create panoramic pictures without the need and expense of position sensors.
Another shortcoming of the current panoramic cameras is how difficult it is to properly overlap a region between two adjacent frames of a panoramic image. Too much overlap results in wasting memory in the digital camera with redundant information.
Another shortcoming with current panoramic cameras is their inability to guide the user where the correct edge overlap is required for creating a panoramic picture alignment from two or more images. Accordingly, a need exists to overcome this problem and to guide the user of a camera using a method and apparatus to overlap two or more images to provide a correct panoramic picture.
Another shortcoming of the current panoramic cameras is the requirement to overlap regions of two or more images. It is common with panoramic image generation to stitch together two or more images. Problems at the boundaries of two images include color distortion, perspective distortion, pixel adjacency and skipped pixels at the edges when joining two or more images. Accordingly, a need exists for a method and apparatus to overcome these shortcomings.
Another shortcoming of the current panoramic cameras is their inability to integrate these mechanisms with other products. The bulk, expense, and complication make these designs difficult to integrate. Accordingly, a need exists for a method and apparatus to allow easy integration of panoramic capabilities into other electronic devices.
Another shortcoming is the inability to easily capture two or more images to create a panoramic scene without the need for expensive computational resources in the camera and without the need for expensive position sensors. Accordingly, a need exists for a method and apparatus to provide a camera which can capture two or more images so as to create a panoramic image.
Another shortcoming is the requirement of having two distinct buffers to transform the captured image from one coordinate system to another coordinate system, such as rectilinear coordinates to cylindrical coordinates. The expense and space required for two buffers for coordinate transformations is undesirable. Accordingly, a need exists to provide a method and apparatus that can transform images from one coordinate system to another coordinate system, without the use of two buffers.
Another shortcoming with current panoramic cameras is the perspective of the series of images relative to each other is lost. One known procedure uses sub-sampling. The picture is scaled down so that the horizontal dimension will match the horizontal extent of the view-port. However, the picture must become a narrow stripe in order to maintain the correct aspect ratio. This will produce a great loss of vertical resolution. Another solution is to scroll the panoramic image horizontally by a fixed amount. In this case no sub-sampling is used, provided that the vertical dimension of the picture will fit the vertical dimension of the view-port. Accordingly, a need exists to provide a method and apparatus to create a moving display of still pictures with perspective without the need to sub-sample or to horizontal scroll.
Still another shortcoming with current panoramic cameras is the requirement that all the image processing electronic circuitry for the final stitching together of one or more images in a series into a single panoramic image is integrated into the camera. Many times, the added expense, the additional weight and the additional size of the electronic circuitry make the camera unwieldy to carry and operate. Moreover, the additional electronic circuitry makes the camera more expensive to manufacture. Accordingly, a need exists for a method and apparatus to enable the preview of a series of adjacent images to form a panoramic, but to enable the final image stitching processing on a remote device such as a personal computer.
A method for converting a rectilinear image and a focal length into a cylindrical image parameterized by a height of the cylinder and an angular distance in a single buffer on a remote processing device. The method, on the remote processing device, comprising joining two or more images together to form a panoramic image with corrected perspective. The rectilinear transformation is "in-place" and requires only one buffer. Color correction and motion estimation is also carried out on the remote device.
In an alternate embodiment, a computer readable medium corresponding to the above method is described.
The subject matter which is regarded as the invention is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other objects, features, and advantages of the invention will be apparent from the following detailed description taken in conjunction with the accompanying drawings.
However, it should be understood that these embodiments are only examples of the many advantageous uses of the innovative teachings herein. In general, statements made in the specification of the present application do not necessarily limit any of the various claimed inventions. Moreover, some statements may apply to some inventive features but not to others. In general, unless otherwise indicated, singular elements may be in the plural and visa versa with no loss of generality.
Actual Next Picture--the picture that is actually captured as the next addition to the set of pictures constituting the Panorama.
Bottom-to-Top Vertical Panorama--a Panorama captured by taking a set of pictures by rotating the camera up (from bottom to top) between each capture, with as little horizontal displacement as possible.
Current Buffer--a cylindrically warped version of the current picture.
Current Picture/Current View/Current Frame--a picture displayed on the camera LCD screen and that is updated in real time. If the LCD screen is not used or if there is no LCD screen, it is the picture that would be captured at any given moment if the capture button was pressed.
Ideal Next Picture--in a Left-to-Right Horizontal Panorama, the picture that would be obtained if the camera was positioned so that the Previous Picture and Ideal Next Picture have an Overlay Part Length equal to the Set Overlay Part Length and no vertical displacement. In a Left-to-Right Horizontal Panorama, the overlay part is on the right of the Previous Picture and on the left of the Ideal Next Picture.
Ideal Position of the Camera for the Ideal Next Picture--The position of the camera that allows to capture the Ideal Next Picture.
Image Stitching--the process of digitally combining scenes taken from different camera orientations.
Left-to-Right Horizontal Panorama--a Panorama captured by taking a set of pictures by rotating the camera clockwise (from left to right) between each capture, with as little vertical displacement as possible.
Overlay Part Length--in a Horizontal Panorama, the width of the overlay part. It is expressed in term of percentage of the whole picture width.
Overlay Part of A Picture--the part of the picture picturing the overlay zone.
Overlay Zone of Two Pictures--the part of a scene that is present in the two pictures.
Panoramic--an image with at least one dimension such as height or width which is greater in dimension of a single capturing device and often involves a series of images. A picture created from a set of pictures and that has at least one dimension bigger than the corresponding dimensions of a source picture.
Preview Strip--a computed image created through digital processing of the overlay part of the Previous Picture and that strives to predict what the overlay part of the Ideal Next Picture will look like.
Previous Buffer--a cylindrically warped version of the Previous Picture.
Previous Picture/Previous Frame--a picture that has already been captured and that is the latest addition to the set of picture constituting the Panorama.
Right-to-Left Horizontal Panorama--a Panorama captured by taking a set of pictures by rotating the camera anticlockwise (from right to left) between each capture, with as little vertical displacement as possible.
Set Overlay Part Length--a constant Overlay Part Length for each pair of pictures constituting the Panorama. The Set Overlay Part Length is the fixed length chosen for a given Panorama.
Top-to-Bottom Vertical Panorama--a Panorama captured by taking a set of pictures by rotating the camera down (from top to bottom) between each capture, with as little horizontal displacement as possible.
Referring now in more detail to the drawings in which like numerals refer to like parts throughout several views, shown in
One or more user inputs via the LCD Controller 128 provides user control over camera functions such as the orientation of the panoramic e.g., horizontal or vertical, and the direction of movement such as a Left-to-Right Horizontal Panoramic, a Right-to-Left Horizontal Panoramic; a Top-to-Bottom Vertical Panoramic; and a Bottom-to-Top Vertical Panoramic. Other user input such as the optional features and desired effects and to set system parameters such as:
Panorama mode on/off.
Panorama parameters.
Left-to-Right Horizontal mode.
Right-to-Left Horizontal mode.
Top-to-Bottom Vertical mode.
Bottom-to-Top Vertical mode.
Set Overlay Part Length.
Preview display on/off.
Mixing mode parameters.
Alpha blending on/off.
Alpha blending parameters such as alpha blending ratio.
Interlaced block mode on/off.
Interlaced block pattern selection.
In another embodiment, many of the components of
Turning now to
Turning now to
The computed Preview Strip 702 can be displayed on the digital camera 100 in various way to help the user in precisely placing the camera in the desired position. One way is to alpha blend (with adjustable coefficient) the preview with the current display of the scene on the LCD 126. In another embodiment, the interlace some blocks of the preview with the displayed Current View on the digital camera 100. Further information on blending is described below.
The stitching overview of
The process flow of stitching is divided into two cases: (1) stitching the first frame, and (2) stitching the subsequent frames. The process flow begins, step 1002 and a determination if the first frame has been captured, step 1004. If the frame is the first frame, such as A of
The overlay region 1818, also referred to as the Preview Strip 702, contains a picture obtained from the previous picture and which and which has been transformed digitally in order to match the perspective for the ideal current picture. This overlay picture contained in the overlay region 1818 is used to guide the user in position in the camera so that he/she will capture a current picture as close as possible to the ideal current picture. The image contained in the overlay region 1818 can be obtained from the previous picture in cylindrical representation or from the previous picture in rectangular representation. Obtaining the overlay picture from the cylindrical representation does not require any additional processing block, for it is the same transformation used in the Motion Picture Playback Module described further in Section 6 "Motion Play-Back of Still Picture That Have Been Previously Save", below. However, in the this embodiment, the overlay region 1818 is in a rectangular representation. The use of a rectangular representation yields a better picture quality since only one digital transform is used while two are needed when using the cylindrical source. The use of an in-place cylindrical transform, means that the rectangular coordinate picture is overwritten by the cylindrical coordinate picture. And it is necessary to perform the computation and saving of the overlay region 1818 in the overlay buffer prior to or before the in-place rectilinear-to-cylindrical transform occurs. Once the overlay region 1818 is estimated to correct perspective for the next image is calculated, step 610. The parameters for stitching are set as follows:
preFarEdge=0;
preNearEdge=length;
prevDispl=default.
Where length is the length of overlap between the images, and default is a displacement value whose value is set to be greater than zero and less the length of overlap. The value is the displacement along normal to the direction of orientation for the panoramic. Stated differently, for a horizontal panoramic, the default would be the maximum vertical displacement. And the stitching for this first frame is complete, step 1016. The Current View is loaded into the curBuffer 1808, step 1019, a preview of the curBuffer 1808 into the overlay region 1818 of the Current Buffer 904 is done to assist the user in aligning the two images at the region of overlap. Returning to
Next, the prevBuffer 1802 from prevFarEdge 1804 to preNearEdge 1806 with preDisp (previous displacement or previous motion estimation ) is saved, step 1030. The region of prevBuffer 1802 between prevFarEdge 1804 and prevNearEdge 1806 is save out to image memory, such as storage media 142. Since all the prevBuffer 1802 would have been saved out a this time, the contents of Previous Buffer 1602, that is the image prevBuffer 1802 are no longer needed. Now the curBuffer 1808 becomes the prevBuffer 1802 and the prevBuffer 1802 becomes the curBuffer 1808. Stated differently the curBuffer 1808 and prevBuffer 1802 are swapped. Finally, the system parameters are set as follows:
prevFarEdge=length-curFarEdge;
prevNearEdge=length;
prevDisp=curDisp.
Now further details on the Picture Stitching Device 124 are described. The description begins with an exemplary hardware implementation followed by examples of the processes implemented by each hardware section.
There are several methods to mix the preview strip with the Current View. Methods that are discussed are: Alpha Blending; Alpha Blending with Progressive Ratio; Interlacing; Alpha Blending & Interlacing.
The alpha blending mixing between the preview strip and the Current View is illustrated in FIG. 11. The preview strip is alpha-blended with the overlap part of the real-time Current View and displayed. The alpha-blending operation is done with the following algorithm:
Result=alpha×Preview_Strip+(1-alpha)OverlapPart_of_Current_View.
The alpha ratio of the blending can be user selected of fixed. The alpha blending can be uniform over the preview picture or varies over the overlay part as shown in
Blocks of the preview picture are interlaced with the real-time Current View displayed on the camera. Several block sizes can be used, including blocks as wide as the preview picture (blocks of lines) and blocks as high as the preview picture (blocks of columns). The size of the blocks does not need to be uniform.
Both alpha Blending and Interlacing can be used as shown
The Panorama is saved in fixed size strips as illustrated in FIG. 20. The use of saving the image as strips helps facilitate the playback of the strip, as described in Section 6 "Motion Play-Back of Still Pictures That Have Been Previously Stored," below. The saving process is managed by a Panorama Saving Module that maintains a working buffer the size of a single strip. Each time a region of prevBuffer 1802 is saved, as many strips as necessary are saved out, and the remainder is stored in the working buffer (to be saved out the next time). After the last curBuffer 1808 is saved, the (partial) working buffer is saved out.
In an alternate embodiment, everything except the minimum circuitry of the picture stitching device 124 to enable alignment preview 2104 can be located on a remote processing device such as a personal computer or other microprocessor-based device. The use of a remote processing device, reduces the size of the electronic circuitry in picture stitching device 124, the weight of the picture stitching device 124 and the complexity and associated cost of manufacturing the picture stitching device 124. In this embodiment, any or all of the following components may be in a remote processing system, including: the displacement estimation 2106, the color correction parameter estimation 2108, and the stitching & blending 2110 can be located or implemented in a remote microprocessor-based system (not shown). The interface to the remote microprocessor-based system may be through the Serial I/O 136 or Storage Media 142 that may be removable and coupled to the remote microprocessor-based system.
A.1. Alignment Preview Architecture
A.2. Perspective Correction in Alignment Preview
An overview of the picture stitching device 124 is now described for the region of overlap.
The part of each picture (Previous Picture 2302 and Current Picture 2304 that is also depicted in the other picture is called the overlap region. Although the scene captured in the Previous Picture 2302 and the Current Picture 2304 is the same in the overlap region 2306 because of a difference in perspective. The Alignment Preview 2304, generates a preview of the Current Picture 2304 by correcting the perspective of the overlap region 2306 of the Previous Picture 2302 to conform with the perspective of the Current Picture 2304.
The process of perspective correction during the alignment previous involves the following steps:
(a) Mapping each of the pixels of the Previous Picture 2302 to an X-Y coordinate;
(b) Mapping each of the pixels of the Current Picture 2304 to an X-Y coordinate so that the x-axis is the center of the image plane of the current picture along the direction of the panning motion of the digital camera 100 and so that the y-axis is perpendicular to the x-axis and lies in the same image plane. This is shown graphically in FIG. 23.
(c) Calculating the rotation angle δθ based on the amount of overlap in the preview area along the x direction.
(d) Calculating the rectilinear x-coordinate transformation based on δθ to project or perspectively warp, the Current Picture 2304 onto Previous Picture 2302.
This is shown graphically in FIG. 24.
(e) Calculating the y-scanline resealing.
Steps c, d, and e above are all now shown mathematically with reference to
In this example, the overlap region 2306 of the Current Picture 2304 indicates the overlay region 2306 that is derived from the Previous Frame 2304; in this case, the camera 100 rotating clockwise.
To calculate the rotation angle δθ based on x_ovlp 2310:
The width of this overlap region 2306 is a system parameter. Given the width of the overlap region 2306, the rotation angle required to produce an overlap of that width is calculated. The width of the overlap region is specified by the location of the region's rightmost (innermost) edge x_ovlp 2310.
The transform induced on the Previous Picture as a result of the 3D rotation is a uniform resealing of each vertical scanline independently. (In the case of camera tilt, the transform is a uniform resealing of each horizontal scanline independently). This transform is described by: (a) the location of the source scanline corresponding to each destination scanline; (b) the scale factor for each scanline; and (c) column scaling. Calculating the x-coordinate transformation:
x'--src=(x--dst×cos δθ)+(f×sin δθ), f'--src=(-x--dst×sin δθ+(f×cos δθ).
Solving for x-src:
The location of the source scanline (x_src) is dependent on the rotation angle (δθ) the focal length (f), and the destination scanline location (x_dst). The equations above describe a 2D plane rotation of the x and f axis; the y axis is left unchanged. The source scanline location (x_src) is calculated by projecting onto the image plane of the Previous Frame. Calculating y-scanline resealing:
This equation shows that y_src is a uniform resealing of y by a factor that depends on x_dst, the rotation angle δθ, and the focal length f. Like x_src, y_src is computed by projecting onto the image plane of the Previous Frame.
Note that there are likely to be instances where the overlap region 2306 of Current Picture 2304 cannot be computed from overlap region 2306 of the Previous Picture 2302, according to the present invention. This is shown as areas 2502 and 2504 of FIG. 25.
It should be understood that all trigonometric calculations can use look-up tables as required for faster implementation. All sections of the picture stitching device 124 use a `closest` coordinate approach when the result of a coordinate computation is not integers. Another approach is to read the value of the neighboring pixels and perform an interpolation. The location of the source scanline (x_src) is calculated based on the rotation angle (δθ), the focal length (f), and the destination scanline location (x_dst). The principle is that, for any given column x_dst of the Preview Area 602, the location in the Previous Buffer 902 is computed based on the corresponding x_src column. The given column x_dst the scaling factor:
The column scaling is performed by reading a column from the Previous Buffer 902 and write a scaled version of this column in the Current Buffer 904.
A.3. Fast Buffering During Perspective Correction
Turning now to
B.1. Algorithm for Rectilinear-to-Cylindrical Transform (Cylindrical WARP in Place)
During the left-to-right pass, each new destination vertical scanline is computed by resealing a scanline somewhere to the right of it (or even at the same location). Since the image representation of the current implementation could be subsampled horizontally, a buffer of two column of pixels, the current scanline and the next (right), is needed. When using a YcrCb format for the pictures were Chroma samples (Cr: Chroma red and Cb: Chroma blue) are decimated. This is because the original subsampled chroma samples could be required after they have been modified (rescaled). Each Chroma sample is shared between two successive Luma (Y) samples. At the end of each iteration of the pass, the buffers are updated. If the source vertical scanline is either the current or the next scanline, the buffered copies are used instead of being derived from the Current Picture.
In another embodiment, interpolation is used to create a column of source pixel (in the case when the computed source column coordinate does not correspond exactly to a real source column coordinate, the closest real source column is used. The use of the closest real source column is an approximate solution that yields average picture quality. To perform interpolation, several source columns are used so a few columns are buffered for later interpolation.
The right-to-left pass proceeds analogously, the only difference is that the source scanlines are computed by resealing scanlines somewhere to the left of current scanlines. A similar two-scanline buffer that contains the current and the next (left) is also required. The last (leftmost) scanline could require the scanline to the left of it. If so, the copy buffered at the start should be used in place of the Current Picture.
B.2. Calculating the X-coordinate Transformation
The location of each source vertical scanline (x_src) depends on the destination scanline (θ) and the focal length (f). The coordinate θ varies linearly from θ_min to θ_max as shown in the following equations.
Where
x_src=the coordinate of a column in the source picture
θ=the Angle coordinate of a column in the transformed picture
The transformation relation:
where f is the focal length used to capture the source picture.
x_src varies from -w/2 to w/2, and is equal to 0 at the center of the picture. θ varies from θ_min to θ_max and is equal to 0 at the center of the picture. Note that θ_max=f×tan (w/2)=-θ_min.
For storage purpose, a column equivalent is defined to the angle coordinate and define x_dst is defined such that:
This definition of x_dst ensure the following desirable property:
for θ=0, x_dst=0;
for θ=θ_max, x_dst=f×tan(θ_max)=w/2
for θ=θ_min, x_dst=f×tan(θ_min)=-w/2
i.e. x_dst is centered on the center of the destination scan line and varies from -w/2 to w/2, just like x_src.
Using this definition it follows that:
to simplify, this can be written
x_src=f×tan(θ)×x_dst), where f and C are constants
By studying the function x_src(x_dst), it is follows that:
for any x_dst between 0 and w/2, x_dst>=x_src(x_dst)>=0
for any x_dst between -w/2 and 0, 0>=x_src(x_dst)>=x_dst
Returning to the in place transformation, in order to avoid `gaps` or overwriting in the destination image, for each column (i.e. for each x_dst) of the destination scanline, we find the closest corresponding column (i.e. x_src) in the source image.
It has been show that:
for any x_dst between 0 and w/2,
x_dst>=x_src(x_dst)>=0
This means that, for every x_dst, the information required is located in the source image at column coordinate x_src, which is smaller or equal to x_dst, never bigger than x_dst. In turn, this means that, for any given x_dst, the area of the SOURCE image situated for column coordinate bigger than x_dst is not needed.
By scanning the destination image between 0 and w/2 in decreasing order (i.e. starting at w/2 and finishing at 0).
at time t1, compute x_dst1 using x_src1<=x_dst1
at time t2>t1, compute x_dst2 using x_src2<=x_dst2
and x_dst2<x dst1 since the scan is progressing in decreasing order.
Therefore, it follows:
All the information of the source image situated at column coordinate bigger than x_dst, is deleted, since it will not be needed for the creation of the current x_dst column of the destination image nor for the creation of any column later in the processing.
Given proper care, the discarded area of the source image can be used to store the destination image itself in order to save the cost of a separate buffer.
When doing the overwriting of the source image by the destination image, some special care must be taken, in particular:
since the function x_src(x_dst) will most of the time not return an integer value, other methods may be used to find the closest source column matching x_src. For example, interpolating a source column based on adjacent source columns, a small number of source columns around x_dst should be buffered and not overwritten as long as they can be necessary in the computation.
when using a Y, Cr, Cb format (in which Cr and Cb samples are decimated, i.e.: shared between several Y sample columns) for the source image, proper buffering of Y columns must be done around x_dst in order not to loose relevant information.
In the region between -w/2 and 0, the same reasoning apply if, between -w/2 and 0, the destination image is scanned in increasing order (i.e. starting at -w/2 and finishing at 0). So, to perform the in place cylindrical transformation, it is necessary to split the picture processing in two part, one from -w/2 to 0 and the other one from w/2 to 0. Again, some special care (buffering of a few columns around x_dst) must be taken around x_dst=0.
Although only a small number of columns must be buffered and the size of these buffers is small compared to the size of a complete image buffer. This means that using in place transform save an appreciable amount of memory, and the benefits are proportional to the size of the images used.
B.3. Calculating Y-scanline Rescaling
This equation shows that the destination vertical scanline is a uniform rescaling of the source scanline whose scale factor depends on the focal length (f) and the horizontal coordinate (θ). The scale factor is normalized such that the scale factor corresponds to unity at either the left (θ_min) or the right edge (θ_max).
C.1. Algorithm for Displacement Estimation (Motion Estimation)
Motion estimation is performed on a pair of images in cylindrical coordinates. Motion estimation is carried out in four steps:
(1) Horizontal and Vertical Downsampling;
(2) One-Dimensional High Pass Filtering;
(3) Computation of Displacement of Dominant Direction; and
(4) Computation of Displacement in Other Direction.
During the first step, each image is horizontally and vertically downsampled. Since two images are being downsampled, a total of four downsampled images are generated. Each of the four downsampled images is then high pass filtered in the horizontal direction. After high pass filtering, the displacement in the dominant direction is estimated using the appropriate pair of downsampled images. For example, if the horizontal displacements are thought to be larger than the vertical displacements within their respective ranges, then the horizontal displacement is estimated first using the vertically downsampled images. Note it is impossible to be sure if the horizontal displacement are larger since the displacements have not been calculated yet, however in a horizontal panorama, the horizontal displacement are naturally larger than the vertical displacement because it is easy to keep the camera more or less level while it is more difficult to make a mistake on the horizontal positioning of the camera for each shot. At this point, in one embodiment, the assumption is that the vertical displacement is zero. This is possible because (a) the vertical displacement is assumed to be small, and (b) the horizontal displacement estimation is carried out on vertically downsampled images. After the horizontal displacement is obtained, the vertical displacement is estimated using the horizontally downsampled images. In this case, we take into consideration the previously estimated horizontal displacement by translating the horizontally downsampled images appropriately.
a. Horizontal and Vertical Downsampling
b. One-Dimensional High-Pass Filtering
One-Dimensional High Pass Filtering is performed next on each of the downsampled images (a total of four: two per image). This high pass filtering is needed to make the error measure robust (invariant) to global illumination changes. One-dimensional high pass filtering is carried out in the horizontal direction only. Since the horizontally downsampled result has been mirror reflected, one-dimensional high pass filtering in the horizontal direction is the same as filtering in the vertical direction of the unreflected result. The current choice of filter coefficients is [-1, 2, -1].
c. Estimating the Horizontal and Vertical Displacements
The motion estimation required for the digital camera 100 is larger in one direction than the other. When the Panorama is horizontal, the horizontal displacement is assumed to be larger than the displacement in the vertical direction. Conversely, when the Panorama is vertical, the vertical displacement is assumed to be larger than the displacement in the horizontal direction. Thus, and because of the downsampling, we can first compute the displacement in the dominant direction, assuming that the displacement in the other direction is zero. After this displacement is determined, the displacement in the minor direction is computed taking into consideration the displacement in the dominant direction. Nevertheless, displacements are always calculated in the horizontal direction because of the prior rotation of the horizontally downsampled scanlines.
C.2. Calculating the SAD Between Images
For each displacement dx:
SAD[dx]=0.
For each scanline y:
For each displacement dx:
SAD[dx]+=ScanlineSAD(dx, Image1Scanline, Image2Scanline).
Note that the ScanlineSAD function computes the SAD between pairs of scanline only over the overlap region. Since the overlap region is of varying size, the scanline SAD is also normalized; specifically, the SAD/pixel is computed. Alternatively, if the window over which the SAD is computed by ScanlineSAD is held fixed, then normalization is unnecessary. Note that the ScanlineSAD for all the displacements within the search range could be computed in parallel.
Although SAD is shown, it is important to note that other methods exists to estimate the difference between the two pairs of images. For example, correlation is another method, although more computationally intensive, that can be used in place of SAD. Still other methods exists to accomplish the same results as SAD know to those of average skill in the art.
C.3. Determining the Optimal Displacement
The required operations are implemented by the Displacement Estimation block depicted in FIG. 34.
If the pictures have to be stitched along the horizontal direction, then the displacement along this direction (the dominant one) is computed. The vertical estimation will be computed as a second step. On the other hand, if the dominant direction is the vertical one, then the displacement along this direction will be computed first. The assumption in this embodiment is that the dominant direction is the horizontal one, however it is important to point out again that all the teachings in the current invention apply to vertical panorama image capturing as well. The downsample blocks compute the two sub-sampled pictures along the vertical direction and store the result in the respective buffers. Then these pictures are preprocessed (for ex. an high pass filter is applied to them) and the Sum of the absolute differences is computed. Further details on this algorithm are described in the section below entitled Algorithm for Image Compositing.
D.1. Color Correction Architecture
D.2. Algorithm for Color Correction Estimation
The color correction model that is adopted in the Camera 100 involves brightness and contrast histogram matching. Other more sophisticated techniques exist but histogram matching was chosen because of its independence on motion estimation results and could therefore be computed in parallel.
Denote I_prev as a color channel of the previous buffer (prevBuffer 1802), and I_cur as the same color channel of the Current Buffer (curBuffer 1808). Assume a default overlap between the previous and Current Buffers; this default could be the default position of the Current Buffer with respect to the previous buffer. Within the area of overlaps in the two images, compute:
The brightness and contrast to apply to the Current Buffer to match the previous buffer is given as:
Brightness=E_prev-Contrast×E_cur
Contrast=sqrt(Var_prev/Var_cur)
Instead of color correcting the Current Buffer only, we apply color correction to both buffers equally using the following equations:
Color correction is later applied according to the following equations:
This color correction technique is applied to each color channel independently. For example, if the buffers are YCC, separate brightness and contrast parameters for each of the channel is calculated.
D.3. Algorithm for Color Correction
In this section, a description of the color correction that is applied to the previous and Current Buffers. The parameters of the color correction are the respective brightness and contrast adjustments for each color channel that was computed earlier by matching the buffers' histograms.
Turning now to
Color correction is applied to varying degrees in different parts of each buffer. Within the region of overlap, color correction is applied fully (β=1); outside of the region of overlap, color correction is applied less further away from the overlap (0<=β<1).
Brightness_prev=Brightness/sqrt(Contrast)
Contrast_prev=1/sqrt(Contrast)
Brightness_cur=Brightness/sqrt(Contrast)
Contrast_cur=sqrt(Contrast).
A variant of this scheme does not apply full color correction even within the overlapping region. Instead, only up to 75% of color correction is ever applied. Thus, beta ranges from 0 to 0.75 outside of the overlapping region, and is 0.75 within. Using this technique, the previous and Current Buffers are not sufficiently color corrected to match each other. This is acceptable because the subsequent image compositing step transitions smoothly the previous buffer into the Current Buffer. Not completely color correcting the two buffers is useful as it produces a smoother color transition between the two buffers.
E.1. Image Splicing Architecture
E.2. Algorithm for Image Compositing
Only the overlap region between the previous and Current Buffers are composited. The two buffers are composited according to the following equation:
where a is a weighting factor that varies linearly between one and zero as shown in FIG. 41.
E.3. Algorithm for Image Splicing
This section describes a modification of the image compositing technique described earlier. During image compositing, the previous and Current Buffers are alpha-blended within their region of overlap. While this results in a smooth transition between the two buffers, it produces ghosting when the content in the two buffers differ. For example, if a person is in the overlap region within one buffer and not the other, a ghost-like reproduction of that person will be present in the final Panorama. If the compositing takes place over a narrower region of the overlap region to the left or to the right of the person, then the resulting.Panorama will either contain the person entirely or not include the person (respectively).
Turning now to
F.1. Algorithm for Cylindrical to Rectilinear Transform
Turning now to
Like the Rectilinear to Cylindrical Transform, the Cylindrical to Rectilinear Transform uniformly rescales each vertical scanline in the image independently. Thus, the transform is described by: (a) the location of the source scanline corresponding to each destination scanline, and (b) the scale factor for each scanline.
F.2. Calculating the X-coordinate Transformation
The location of each source vertical scanline (q_src) depends on the destination scanline (x_dst), the focal length (f), and the origin (θ_origin).
F.3. Calculating Y-scanline Rescaling
Each vertical scanline is a uniformly rescaled copy of the original. The scale factor is unnormalized by the factor y'_scale_min that was applied in the forward transform.
Thus, the scale factor depends on the location of the destination scanline (and ultimately, the location of the source scanline), and the focal length. The denominator of y'_scale can be precomputed as a look-up table, indexed by the location of the destination scanline (x_dst).
The digital camera has previously stored images such as images A, B, C, D of
Turning now to
Speed of motion.
Frame Frequency.
Raster Structure: Interlaced/Progressive.
ViewPort Horizontal and Vertical (Xv-Yv) dimension. Shown is a viewport (the rectangle with θ_origina at is venter where Xv and Yv are the viewport dimensions.
Picture Horizontal and Vertical (Xv-Yv) dimension.
Source Picture Reference System: Cylindrical, Planar, Spherical.
Picture Starting address.
Focal Length (f) of the optic used to take the picture.
The picture information is provided to the MPB 4506 by the data line 4512 and the MPB 4506 processes them according to the settings 4514.
Now an example is provided in order to describe how the MPB 4514 works.
The MPB is described now based on the following assumptions: (1) Raster Structure: Interlaced; and (2) Source Picture Reference System: Cylindrical.
Depending on the speed of the motion to be simulated, an offset 468 must be added to the address related to the pixel position along the horizontal direction of source picture. This offset 4608 depends on the Raster structure. For example if the raster is interlaced this offset 4608 must be updated for every field. On the other hand, if the raster is progressive, this Offset must be updated every frame. Where f represents the focal length. Equations (1), (2) and (3) above can be implemented in a variety of hardware and software combinations, including implementing the mathematical functions with a look up table, but this is not restrictive for the invention.
Other embodiments are possible. For example, if the input picture is in planar coordinates, equations (1), (2) and (3) do not implement any transformation in the MPB 4506. On the other hand if the input picture in spherical coordinates the MPB 4506 implements a different set of transforms. The physical address of a picture coordinate is used to retrieve a pixel from the memory. Due to the nature of the transform, it is possible the location Xs and Ys does not correspond to a pixel already existing on the source image. This location can be between to pixels. To recover this drawback, the Pixel Processor block implements an interpolation algorithm in order to compute the pixel value at the position Xs, Ys. Moreover the Picture Processing 4812 implements the down-sampling along the vertical direction in order to fit the vertical size of the viewport.
One architecture of the Picture Processing 4812 is depicted in FIG. 51. And one architecture of the Vertical Sub-Sampling 5102 is depicted in FIG. 52. The vertical Sub-Sampling 5102 requires some Line Memories (LM) and Pixel Delays (PD) in order to implement the processing window required by the particular Interpolation algorithm implemented by the SS_Interp block. Some of those algorithms require the Field/Frame Signal too. The Interpolation block, computes the value of the pixel at the Xs Ys position starting from the available ones in the source picture. A possible implementation of the Interpolation 5104 using a Cubic Interpolator is described in
Although a specific embodiment of the invention has been disclosed, it will be understood by those having skill in the art that changes can be made to this specific embodiment without departing from the spirit and scope of the invention. The scope of the invention is not to be restricted, therefore, to the specific embodiment, and it is intended that the appended claims cover any and all such applications, modifications, and embodiments within the scope of the present invention.
Mancuso, Massimo, Teo, Patrick Cheng-San, Lusinchi, Emmanuel
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